# Etsy Keyword Suggestions - what Etsy's search box completes (`vital_tuxedo/etsy-keyword-suggestions`) Actor

Etsy's own search suggestions for your seed keywords, from the public endpoint the etsy.com search box uses: every completion, expanded letter by letter (seed + a-z, 0-9) and optionally one level deep. One row per unique suggestion with its seed, query and position. No login, no invented volumes.

- **URL**: https://apify.com/vital\_tuxedo/etsy-keyword-suggestions.md
- **Developed by:** [Stephen Psaradellis](https://apify.com/vital_tuxedo) (community)
- **Categories:** Developer tools, E-commerce
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Etsy Keyword Suggestions

What Etsy's own search box completes your keywords to, as a dataset: one row
per unique suggestion, with the seed it came from, the exact query that
produced it, and its position in Etsy's list.

Etsy completes a partial query from what buyers actually type. That makes
its suggestions the closest public thing to a demand signal Etsy offers: a
phrase Etsy completes is a phrase buyers search, and a seed with no
completions is a phrase nobody types. This actor reads the public
suggestions endpoint the etsy.com search box calls, expands every seed
letter by letter (`candle a`, `candle b`, ... `candle 9`) to surface the long
tail, and can go one level deeper by querying every suggestion it found as a
seed of its own.

### What you get

One dataset row per unique suggestion:

| field | meaning |
|---|---|
| `keyword` | the suggestion, exactly as Etsy returned it |
| `seed` | the seed keyword it was reached from |
| `query` | the exact query sent to Etsy that returned it |
| `position` | 1-based position in that query's list (Etsy's order) |
| `depth` | 0 seed query, 1 letter-by-letter expansion, 2 discovered suggestion queried as a seed |
| `categories` | category hints Etsy attached, when any |
| `simplified_queries` | Etsy's simplified forms of the query, when any |
| `read_at` | when the query was answered (UTC) |

The key-value store also gets a `RUN_SUMMARY`: seeds, queries sent, empty
answers, suggestions seen, unique rows pushed, and what stopped the run if a
cap or a block did.

### Input

- **keywords** - the seeds to expand. One query each, plus 36 more per seed
  when expanding.
- **expand** - also query each seed followed by a space and each of a-z, 0-9.
  On by default. This is where the long tail comes from.
- **depth** - 0 seeds only; 1 seeds plus expansion; 2 also query every
  suggestion found as its own seed, one level deep.
- **maxQueries**, **maxSuggestions** - caps on requests sent and unique rows
  pushed. Defaults 2,000 and 10,000; 0 is unbounded.
- **concurrency**, **timeoutSecs** - how the requests are paced.

### Pricing

Pay per event. `query` is charged once per request sent to Etsy;
`suggestion-row` once per unique suggestion pushed. A suggestion seen again
under another query is not charged again, and an empty answer costs one
query and no rows. With the defaults, 10 seeds at depth 1 is at most 370
queries and about 1,500 rows.

### What it does not do

It does not sign in, does not open listing or shop pages, and does not
invent search volumes - Etsy publishes none, and the position within one
query's list is recorded as an ordinal, nothing more. Suggestions vary by
season and region; the rows say when they were read.

### Running locally

```
npm install
npm start
```

Input is read from `storage/key_value_stores/default/INPUT.json`; the
dataset lands under `storage/datasets/default/`.

# Actor input Schema

## `keywords` (type: `array`):

The keywords to expand. Each is sent to Etsy's search-suggestions endpoint as typed; with Expand on, each is also sent followed by a space and every letter a-z and digit 0-9 (36 more queries per seed).

## `expand` (type: `boolean`):

Also query each seed followed by a space and each of a-z, 0-9. This is what surfaces the long tail ("candle w" -> "candle warmer", "candle wedding favor"). On by default; 36 extra queries per seed.

## `depth` (type: `integer`):

0: query the seeds only. 1: seeds plus their letter-by-letter expansion (when Expand is on). 2: additionally query every suggestion found so far as a seed of its own, one level deep. Depth 2 can be hundreds of queries per seed; bound it with Max queries.

## `maxQueries` (type: `integer`):

Stop after this many suggestion requests. 0 means unbounded. Each request is one query event.

## `maxSuggestions` (type: `integer`):

Stop after this many unique suggestions have been pushed. 0 means unbounded. Each unique suggestion is one suggestion-row event.

## `concurrency` (type: `integer`):

How many suggestion requests are in flight at once. Keep it low; Etsy is asked politely.

## `timeoutSecs` (type: `integer`):

A request that does not answer within this many seconds is retried, then recorded as an error.

## Actor input object example

```json
{
  "keywords": [
    "candle",
    "wall art"
  ],
  "expand": true,
  "depth": 1,
  "maxQueries": 2000,
  "maxSuggestions": 10000,
  "concurrency": 4,
  "timeoutSecs": 15
}
```

# Actor output Schema

## `suggestions` (type: `string`):

Every unique suggestion, one row each, with its seed, the exact query it came from, its position and depth.

## `runSummary` (type: `string`):

Counts for the run: seeds, queries sent, empty answers, suggestions seen, unique rows pushed, and what stopped the run if a cap or a block did.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "keywords": [
        "candle",
        "wall art"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("vital_tuxedo/etsy-keyword-suggestions").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "keywords": [
        "candle",
        "wall art",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("vital_tuxedo/etsy-keyword-suggestions").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "keywords": [
    "candle",
    "wall art"
  ]
}' |
apify call vital_tuxedo/etsy-keyword-suggestions --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,vital_tuxedo/etsy-keyword-suggestions"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/TUBe8xP47cVWkvgNz/builds/K135MAvmVdIb1Mc4X/openapi.json